As the necessity for safety and aesthetic of nightscape have arisen, the importance of nightscapes (i.e., nighttime landscape) planning has garnered the attention of mainstream consciousness. Therefore, this study was to suggest the guideline for nightscape planning using electroencephalography (EEG) technology and survey for recognizing the characteristics of a nightscape. Furthermore, we verified the electroencephalography (EEG) method as a tool for landscape evaluation. Therefore, this study analyzed the change of relative alpha wave and relative beta wave and perceived fear of participants depending on twelve nightscape settings (four types of settings: Built nightscape images group with an adult; Built nightscape images groups without an adult; Nature-dominant nightscape images with an adult; and Nature-dominant nightscape images without an adult). Our findings indicate that the most fearful nightscape setting was recorded in Built nightscape images groups without an adult figure in perceived fear result depending on four types of nightscape settings. In Nature-dominant nightscape images, on the other hand, the nightscape setting with an adult figure was more fearful than the setting without an adult. The interaction effect between landscape type (built and nature-dominant) and adult presence towards perceived fear was verified and it showed that the image with adult affects landscape type. For electroencephalography (EEG) results, several brain activities in the relative alpha and beta wave showed significant differences depending on nightscape settings, which situates electroencephalography (EEG) as an invaluable tool for evaluating landscapes. Based on our physiological electroencephalography (EEG) experiment, we provide a new analytic view of the nightscape. The approach we utilized enables a deeper understanding of emotional perception and fear among human subjects by identifying the physical environment which impacts how they experience nightscapes.

This study examines the microclimate pattern and related spatial perception of urban green stormwater infrastructure (GSI) and the stormwater management landscape, using rain gardens as a case study. It investigates the relationship between different rain garden design factors, such as scale, depth, and planting design, and their effects on microclimate patterns and human spatial perception. Taking an area in Blacksburg, Virginia, as the study site, twelve rain garden design scenarios are generated by combining different design factors. The potential air temperature, relative humidity, and wind speed/direction are analyzed through computational simulation. Additionally, feelings of comfort, the visual beauty of the landscape, and the overall favorite are used as an evaluation index to investigate people’s perception of various rain garden design options. The study found that a multilayer and complex planting design can add more areas with moderate temperature and higher humidity. It also significantly improves people’s subjective perception of a rain garden. Furthermore, a larger scale rain garden can make people feel more comfortable and improve the visual beauty of the landscape, highlighting the importance of designing larger and recreational bioretention cells in GSI systems. Regarding depth, a relatively flatter rain garden with a complex planting design can bring stronger air flow and achieve better visual comfort and visual beauty. Overall, by examining the microclimate pattern and related perception of rain gardens, this study provides insight into better rain garden design strategies for the urban stormwater management landscape. It explores the potential of rain garden design in urban GSI and responds to climate change.

The overall purpose of this study was to investigate psycho-physiological variations in human bodies by observing visual images of daytime and nighttime scenery to focus on restorative and recovery effects. Unlike previous studies that have focused on the natural versus built environments, this study aims to compare restorative and recovery potentials between daytime and nighttime. The experiment was conducted by showing a total of 12 images to 60 participants in order to measure the brain response with an electroencephalogram (EEG). As measures of the psychological impact of the images, perceived restorative and recovery scales were used. The self-reported data indicates that daytime sceneries are rated more positively than nighttime sceneries in terms of restorative and recovery effects. According to the EEG results, restorative and recovery feelings have negative relationships with the relative theta band, while positive relationships are shown with the relative alpha band. The correlation analysis between EEG bands and brain regions showed a significant correlation (p < 0.05) with 46 pairs for the daytime scenery stimuli and 52 pairs for the nighttime scenery stimuli. Through the results of the study, we conclude that daytime and nighttime scenery affect restorative feelings and the human brain response through both verbal and non-verbal methods.

As the necessity for safety and aesthetic of nightscape have arisen, the importance of nightscapes (i.e., nighttime landscape) planning has garnered the attention of mainstream consciousness. Therefore, this study is to suggest the guideline for nightscape planning using electroencephalography (EEG) technology and survey for recognizing the characteristics of a nightscape. Furthermore, we verified the EEG method as a tool for landscape evaluation. This study analyzed the change of relative alpha power and relative beta power and self-reporting of participants in order to investigate the correlation between EEG and fear according to twelve nightscape settings. Our findings indicated the corresponding measures of fear vary accordance with whether there was people or not, and the environmental settings (Built Nightscape Images; BNI vs Natural Nightscape Images; NNI). Based on our physiological EEG experiment, we provided a new analytic view of the nightscape. The approach we utilized enables a deeper understanding of emotional perception and fear among human subjects by identifying the physical environment which impacts how they experience nightscapes.

This study examines correlates of preferred future work arrangements among adult residents of the Roanoke Metropolitan Statistical Area, Virginia, a mid-sized U.S. metropolitan region. It focuses on whether remote-work preference varies by sociodemographic characteristics, pandemic-era work-from-home experience, occupational perceptions, and attitudes toward physical interaction. Data were collected through a cross-sectional online survey administered in 2023, during the post-acute pandemic period. After excluding incomplete responses, duplicates, respondents younger than 18 years, cases without verifiable adult eligibility, and cases without verified residence in the study area, the final analytical sample included 636 respondents. Analyses included chi-square tests, Spearman rank correlations, a Stuart–Maxwell test of marginal homogeneity, and an adjusted multinomial logistic regression model. Among respondents with valid preference data, 63.8% preferred fully remote work. Among paired current-preferred cases, preferred arrangements differed significantly from current arrangements, with 87.0% of respondents reporting a directional change preferring movement toward a more remote arrangement. Preferred future work arrangement was significantly associated with age, education, earnings, marital status, housing tenure, perceived work-from-home efficiency, occupational remote-work perceptions, and physical-interaction importance; gender was not significant. Findings indicate substantial but socially differentiated remote-work preference, with implications for workforce planning in mid-sized metropolitan regions.

This study examines correlates of preferred future work arrangements among adult residents of the Roanoke Metropolitan Statistical Area, Virginia, a mid-sized U.S. metropolitan region. It focuses on whether remote-work preference varies by sociodemographic characteristics, pandemic-era work-from-home experience, occupational perceptions, and attitudes toward physical interaction. Data were collected through a cross-sectional online survey administered in 2023, during the post-acute pandemic period. After excluding incomplete responses, duplicates, respondents younger than 18 years, cases without verifiable adult eligibility, and cases without verified residence in the study area, the final analytical sample included 636 respondents. Analyses included chi-square tests, Spearman rank correlations, a Stuart–Maxwell test of marginal homogeneity, and an adjusted multinomial logistic regression model. Among respondents with valid preference data in this nonprobability analytical sample, 63.8% preferred fully remote work. Among paired current–preferred cases, preferred arrangements differed significantly from current arrangements, with 87.0% of respondents reporting a directional change preferring movement toward a more remote arrangement. Preferred future work arrangement was significantly associated with age, education, earnings, marital status, housing tenure, perceived work-from-home efficiency, occupational remote-work perceptions, and physical-interaction importance; gender was not significant. Findings indicate substantial but socially differentiated remote-work preference, with implications for workforce planning in mid-sized metropolitan regions.